scFlow - Merged Multi-Sample Quality-Control Report

Pseudobulk Dimensionality Reduction Plots

These plots represent the pseudobulking of all cells from a sample (“manifest”) into a single point in two-dimensional space. Taken together with the merge summary plots, these may help to identify potential outliers or otherwise problematic samples. Data are visualized with: PCA, UMAP.

PCA

UMAP

Multi-Sample Summary Plots

The multi-sample summary plots below examine key sample quality metrics (total_features_by_counts, total_counts, pc_mito, pc_ribo) across all experimental samples. These plots may highlight samples with marked differences in these metrics and may be used to inform revision of quality-control thresholds. In more extreme cases (e.g. severe outliers, sample degradation, etc.), it may be appropriate to omit sample(s) from an analysis.

These metrics are also visualized across the specified facet variables: group, diagnosis, seqdate

total_features_by_counts

Figure: total_features_by_counts by individual sample (manifest).

total_features_by_counts_vs_group

Figure: total_features_by_counts by group.

total_features_by_counts_vs_diagnosis

Figure: total_features_by_counts by diagnosis.

total_features_by_counts_vs_seqdate

Figure: total_features_by_counts by seqdate.

total_counts

Figure: total_counts by individual sample (manifest).

total_counts_vs_group

Figure: total_counts by group.

total_counts_vs_diagnosis

Figure: total_counts by diagnosis.

total_counts_vs_seqdate

Figure: total_counts by seqdate.

pc_mito

Figure: pc_mito by individual sample (manifest).

pc_mito_vs_group

Figure: pc_mito by group.

pc_mito_vs_diagnosis

Figure: pc_mito by diagnosis.

pc_mito_vs_seqdate

Figure: pc_mito by seqdate.

pc_ribo

Figure: pc_ribo by individual sample (manifest).

pc_ribo_vs_group

Figure: pc_ribo by group.

pc_ribo_vs_diagnosis

Figure: pc_ribo by diagnosis.

pc_ribo_vs_seqdate

Figure: pc_ribo by seqdate.

scFlow v0.3.1 – 2020-01-22 17:45:39